Heron BBH Samples 2018-10-17

This is a jupyter notebook to demonstrate the functionality of the heron-BBH binary black hole surrogate model. The surrogate model is conditioned on numerical relativity data produced by the Georgia Tech group.

PyMC 2017-5-02

Plotting 2017-2-14

Gaussian Processes 2016-12-05

Plot 1: (Draws from) The prior distribution generated by an exponential squared kernel.

4. Using just the NR waveforms as training data 2015-12-04

The approach taken by Moore and Gair is to use the waveform differences between the NR and PN waveforms to train a Gaussian process. Here I investigate whether it is possible to by-pass the PN approximant, and predict a waveform using a Gaussian process trained only from the NR data.